Proteomics, lipidomics, metabolomics: a mass spectrometry tutorial from a computer scientist's point of view

BMC Bioinformatics

Research

Andrew D Mathis¹  John T Prince¹  Dan Ventura²  Rob Smith² 

[1] Department of Chemistry, Brigham Young University, 84606, Provo, USA;Department of Computer Science, Brigham Young University, 84606, Provo, USA;

关键词: Spectral Counting;    Isotopic Envelope;    Analyte Identification;    Data Processing Tool;    Ground Truth Dataset;   

DOI  :  10.1186/1471-2105-15-S7-S9

来源: Springer

【 摘 要 】

BackgroundFor decades, mass spectrometry data has been analyzed to investigate a wide array of research interests, including disease diagnostics, biological and chemical theory, genomics, and drug development. Progress towards solving any of these disparate problems depends upon overcoming the common challenge of interpreting the large data sets generated. Despite interim successes, many data interpretation problems in mass spectrometry are still challenging. Further, though these challenges are inherently interdisciplinary in nature, the significant domain-specific knowledge gap between disciplines makes interdisciplinary contributions difficult.ResultsThis paper provides an introduction to the burgeoning field of computational mass spectrometry. We illustrate key concepts, vocabulary, and open problems in MS-omics, as well as provide invaluable resources such as open data sets and key search terms and references.ConclusionsThis paper will facilitate contributions from mathematicians, computer scientists, and statisticians to MS-omics that will fundamentally improve results over existing approaches and inform novel algorithmic solutions to open problems.

【 授权许可】

CC BY   
© Smith et al.; licensee BioMed Central Ltd. 2014